A survey of 172 open educational datasets from 204 papers across LAK, EDM, and AIED conferences reveals trends, 143 previously uncatalogued datasets, field gaps, and an 8-item PRACTICE checklist for better data publication.
Quixbugs: A multi-lingual program repair benchmark set based on the quixey challenge
5 Pith papers cite this work, alongside 226 external citations. Polarity classification is still indexing.
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PAIR-Bench defines a progressive hinting protocol with failure-region and hint-depth controls to measure LLM code refinement trajectories in detail.
Language models show good calibration when asked to estimate the probability that their own answers are correct, with performance improving as models get larger.
Ranked preference modeling outperforms imitation learning for language model alignment and scales more favorably with model size.
MultiMend augments buggy function context via retrieval and generates multi-hunk patches, fixing 2,227 of 5,501 bugs across six benchmarks in four languages.
citing papers explorer
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Open Datasets in Learning Analytics: Trends, Challenges, and Best PRACTICE
A survey of 172 open educational datasets from 204 papers across LAK, EDM, and AIED conferences reveals trends, 143 previously uncatalogued datasets, field gaps, and an 8-item PRACTICE checklist for better data publication.
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Benchmarking Code Improvement with Progressive, Adaptive, and Interactive Feedback
PAIR-Bench defines a progressive hinting protocol with failure-region and hint-depth controls to measure LLM code refinement trajectories in detail.
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Language Models (Mostly) Know What They Know
Language models show good calibration when asked to estimate the probability that their own answers are correct, with performance improving as models get larger.
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A General Language Assistant as a Laboratory for Alignment
Ranked preference modeling outperforms imitation learning for language model alignment and scales more favorably with model size.
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MultiMend: Multilingual Program Repair with Context Augmentation and Multi-Hunk Patch Generation
MultiMend augments buggy function context via retrieval and generates multi-hunk patches, fixing 2,227 of 5,501 bugs across six benchmarks in four languages.